Android software design for Bluetooth fluorescence spectrometer and its application of vegetable oil type identification

At present, most of the spectrometers used in food detection have some problems such as complex operation, large volume and high cost, which are not conducive to their popularization and application. Therefore, we have developed a small-scale Bluetooth fluorescence spectrometer which can be used for the detection of vegetable oil. The 405 nm semi-conductor laser can be integrated in the spectrometer to excite the fluorescence spectrum of vegetable oil, the spectrum data detected by the spectrometer is transmitted to the Android mobile phone by wireless Bluetooth, and the data is received, displayed and processed by the Android mobile phone software developed by App Inventor. The software can also be used to identify vegetable oils in real time by using machine learning to analyze spectral data on Baidu's AI open platform. In the experiment, the spectrometer collected 600 sets of spectral data of six kinds of vegetable oils, and trained and tested these data by software. The accuracy of oil identification can reach 96.1% . The experimental results show that the spectrometer can identify the kinds of vegetable oil quickly and accurately by using the developed software. It has the advantages of simple operation, high sensitivity, low cost and no pollution to the sample, it has a good application prospect in the field of food safety rapid detection.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1117/12.3046437
Primary Topic
Water Quality Monitoring Technologies
Type
article
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Android software design for Bluetooth fluorescence spectrometer and its application of vegetable oil type identification

Zongjie Bi, Songlin Yin, Ying Guo, Zhaoshuo Tian et al.
Water Quality Monitoring Technologies
article

Android software design for Bluetooth fluorescence spectrometer and its application of vegetable oil type identification

Zongjie Bi, Songlin Yin, Ying Guo, Zhaoshuo Tian, Xiaohua Che, G Fu
article en

Abstract

At present, most of the spectrometers used in food detection have some problems such as complex operation, large volume and high cost, which are not conducive to their popularization and application. Therefore, we have developed a small-scale Bluetooth fluorescence spectrometer which can be used for the detection of vegetable oil. The 405 nm semi-conductor laser can be integrated in the spectrometer to excite the fluorescence spectrum of vegetable oil, the spectrum data detected by the spectrometer is transmitted to the Android mobile phone by wireless Bluetooth, and the data is received, displayed and processed by the Android mobile phone software developed by App Inventor. The software can also be used to identify vegetable oils in real time by using machine learning to analyze spectral data on Baidu's AI open platform. In the experiment, the spectrometer collected 600 sets of spectral data of six kinds of vegetable oils, and trained and tested these data by software. The accuracy of oil identification can reach 96.1% . The experimental results show that the spectrometer can identify the kinds of vegetable oil quickly and accurately by using the developed software. It has the advantages of simple operation, high sensitivity, low cost and no pollution to the sample, it has a good application prospect in the field of food safety rapid detection.

Harbin Institute of Technology (CN)
Zero hunger
Openalex Percentile: Top 78%
Water Quality Monitoring Technologies
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